Q01
Long Text
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Privacy Nutrition Label Comprehension & Trust Survey
Measures how users interpret, evaluate, and act on app privacy nutrition labels using a concept-testing methodology with comprehension checks, trust and usefulness scales, and preference ranking. Suitable for UX researchers, privacy teams, and compliance professionals seeking to optimize label design.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
26 questions · ~4 min
Q02
Multiple Choice
In the past 12 months, have you seen a privacy "nutrition label" (a summary panel showing what data an app or service collects) for any app, website, device, or service?
Q03
Multiple Choice
Where have you encountered a privacy label? Select all that apply.
Q04
Long Text
<p>Please review the following fictional privacy label for "FitTrack," a health and fitness app.</p><p><strong>Data Collected:</strong></p><p>Precise location — Used for route tracking (retained up to 1 year)</p><p>Health & fitness data — Used for app functionality (retained until account deletion)</p><p>Usage analytics — Used for product improvement (retained up to 90 days)</p><p><strong>Data Shared with Third Parties:</strong></p><p>Usage analytics — Shared with analytics providers</p><p>Health & fitness data — Not shared</p><p>Contacts — Not collected</p><p><strong>Security:</strong> Data encrypted in transit and at rest.</p><p><strong>Controls:</strong> You can disable location tracking and delete your data at any time.</p><p>Please review this label carefully before continuing.</p>
Q05
Multiple Choice
Based on the sample label you just reviewed, does FitTrack collect precise location data?
Q06
Long Text
Overall, how useful would this style of privacy label be when deciding whether to use an app?
Q07
Long Text
Rank the following label elements by how important they are to you when deciding whether to use an app (drag to reorder; top = most important).
Q08
Long Text
What, if anything, would make privacy labels more useful or easier to understand?
Q09
Long Text
What is your age?
Q10
Long Text
Thank you for completing this survey. Your feedback will help improve how privacy information is designed and communicated to users like you.
Q11
Multiple Choice
When choosing apps or devices in the past 3 months, how often did you notice privacy labels?
Q12
Multiple Choice
According to the sample label, how long are usage analytics data retained?
Q13
Long Text
How easy or difficult was the sample privacy label to understand?
Q14
Long Text
Realistically, how much time would you spend reading a privacy label before installing an app?
Q15
Long Text
Based on your responses in this survey, please share any additional thoughts or feelings about privacy labels and how they influence your decisions.
Q16
Multiple Choice
Which best describes your gender?
Q17
Multiple Choice
After reading a privacy label, which actions have you taken? Select all that apply.
Q18
Multiple Choice
According to the sample label, are your contacts shared with third parties?
Q19
Long Text
If a product displays this kind of privacy label, how would it affect your trust in that product?
Q20
Multiple Choice
Where do you think privacy labels should appear? Select all that apply.
Q21
AI Interview
We'd like to explore your thoughts on privacy labels in a bit more depth. An AI moderator will ask you a couple of follow-up questions about your experiences and opinions.
Q22
Long Text
If you selected 'Prefer to self-describe,' please share your gender identity (optional):
Q23
Long Text
How likely would you be to choose an app that displays a privacy label like this over one that does not?
Q24
Long Text
In which region do you currently live?
Q25
Long Text
What is the highest level of education you have completed?
Q26
Long Text
What is your current employment status?
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.